These are the *R* functions that we primarily use in SE350:

Function | Description |
---|---|

getwd() | Get the working directory path |

setwd() | Set Working Directory |

dir() | Show the names of the files in the working directory (or folder) |

ls() | List all object in workspace |

read.csv(file,as.is=TRUE) | Import Data from a Comma Seperated Value file |

dim(object) | Give dimensions of an object |

summary(data) | Provide a summary of an object |

class(object) | Give the class of an object (i.e. character, numeric, etc) |

as.factor(character object) | Coerce a Characer object to Factor |

as.character(object) | Coerce a factor object to character |

plot(x,y) | Plot x and y |

c(object1, object2, object3….) | Create a vector of objects |

rep(x,rep=) | Repeat x a certain number of times |

data.frame() | Build a data frame with a number of fectors |

names(dataframe) | Give names of the data.frame |

head(dataframe) | Give the first 5 lines of the data frame |

subset(data,formula) | Subset data by a boolean expression (i.e. Gender==“Male”) |

table(x) | Provide a table of x |

pie(table) | Plot a pie chart of a table |

barplot(table) | Plot a barplot of a table |

aggregate(x~y,data,function) | Aggregate x by y given a function (mean, sum , etc) |

hist(x) | Plot a historgram of x |

boxplot(x) | Plot a boxplot of x |

pairs(numeric columns of a data table) | Produce a pairs plot of |

cor(x,y) | Correlation of X and Y |

lm(x,y,data) | Linear Model of x and y from data |

abline(lm.model) | Add a regression trendline from lm.model to a plot |

summary(lm.model) | Get the basic statistics from lm.model |

predict(lm.model, newdata) | Predict with newday on lm.model |